---
license: apache-2.0
base_model: hZzy/qwen2.5-0.5b-sft-news-IFT
tags:
- alignment-handbook
- ndcg
- trl
- expo
- generated_from_trainer
- trl
- expo
- generated_from_trainer
datasets:
- hZzy/train_pairwise
model-index:
- name: qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-50-5e6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/a6pnerr5)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-50-5e6

This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on the hZzy/train_pairwise dataset.
It achieves the following results on the evaluation set:
- Loss: 223.1421
- Logps: -81.8519
- Logits: -0.6524
- Objective: 224.3911
- Dpo Loss: 114.2648
- Regularize: 224.3911
- Ranking Simple: 0.5083
- Ranking Idealized: 0.5093
- Ranking Idealized Expo: 0.5093

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 12
- total_train_batch_size: 288
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 72.7249       | 0.2834 | 50   | 49.7663         | -92.8163 | -1.3016 | 48.7266   | 25.8845  | 48.7266    | 0.5083         | 0.5093            | 0.5093                 |
| 152.2211      | 0.5668 | 100  | 146.6511        | -80.6726 | -1.2458 | 149.0543  | 74.5413  | 149.0543   | 0.5124         | 0.5093            | 0.5093                 |
| 149.0411      | 0.8503 | 150  | 179.0229        | -81.4258 | -0.9511 | 179.4755  | 89.5257  | 179.4755   | 0.5124         | 0.5093            | 0.5093                 |
| 135.6758      | 1.1337 | 200  | 190.7774        | -83.1371 | -0.8760 | 195.4946  | 98.7297  | 195.4946   | 0.5083         | 0.5093            | 0.5093                 |
| 122.9397      | 1.4171 | 250  | 204.8156        | -81.1880 | -0.8410 | 206.5414  | 104.7900 | 206.5414   | 0.4990         | 0.5093            | 0.5093                 |
| 109.8686      | 1.7005 | 300  | 216.4334        | -82.2344 | -0.6658 | 216.9471  | 109.1882 | 216.9471   | 0.5083         | 0.5093            | 0.5093                 |
| 97.6956       | 1.9839 | 350  | 218.2887        | -81.0804 | -0.6323 | 217.4291  | 109.8084 | 217.4291   | 0.5072         | 0.5093            | 0.5093                 |
| 86.0309       | 2.2674 | 400  | 221.7113        | -83.6082 | -0.5904 | 225.3389  | 115.8749 | 225.3389   | 0.5052         | 0.5093            | 0.5093                 |
| 78.4362       | 2.5508 | 450  | 221.3732        | -82.0743 | -0.6173 | 224.4839  | 116.2117 | 224.4839   | 0.5114         | 0.5093            | 0.5093                 |
| 65.179        | 2.8342 | 500  | 223.8012        | -82.3425 | -0.6892 | 227.1755  | 114.9871 | 227.1755   | 0.5083         | 0.5093            | 0.5093                 |
| 52.3116       | 3.1176 | 550  | 223.6770        | -81.8433 | -0.6290 | 226.7591  | 114.9252 | 226.7591   | 0.5103         | 0.5093            | 0.5093                 |
| 45.9426       | 3.4010 | 600  | 222.4720        | -81.3168 | -0.6183 | 223.1873  | 113.6331 | 223.1873   | 0.5072         | 0.5093            | 0.5093                 |
| 37.3789       | 3.6845 | 650  | 223.4119        | -81.7013 | -0.6355 | 225.2157  | 114.6103 | 225.2157   | 0.5072         | 0.5093            | 0.5093                 |
| 32.7043       | 3.9679 | 700  | 223.5499        | -81.8343 | -0.6585 | 224.4542  | 114.2602 | 224.4542   | 0.5062         | 0.5093            | 0.5093                 |
| 22.8627       | 4.2513 | 750  | 223.7742        | -81.7547 | -0.6564 | 224.6748  | 114.4499 | 224.6748   | 0.5072         | 0.5093            | 0.5093                 |
| 19.3618       | 4.5347 | 800  | 223.2886        | -81.8898 | -0.6540 | 224.4371  | 114.3485 | 224.4371   | 0.5083         | 0.5093            | 0.5093                 |
| 18.3796       | 4.8181 | 850  | 223.1902        | -81.8524 | -0.6522 | 224.4282  | 114.2867 | 224.4282   | 0.5083         | 0.5093            | 0.5093                 |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1